Using New Data to Improve Transit Networks

The transportation ecosystem is changing rapidly. Individuals have new transportation options, and nationwide trends show transit ridership in decline. New technologies, such as automated vehicles, are expected to continue to reshape mobility in the future. In this environment, transit system owners and operators are seeking to adapt their network design and services. Improved data availability and new processing methods can identify ways to improve transit service.

Compared to rail systems, bus networks can be altered at relatively low cost to accommodate changes in demand. Bus network revisions include large-scale overhauls, such as recent redesigns in Houston and Columbus, as well as incremental approaches to bus network change, such as route additions, deletions, and realignments. To make these changes, planners need to understand how the current system is used and where there is potential for improvement.

In recent years, contactless smart card-based automatic fare collection (AFC) systems have become increasingly prevalent. Some agencies, including Utah Transit Authority (UTA) and Chicago Transit Authority (CTA), also accept payment via contactless credit and debit cards. These technologies allow cards to be tracked over time. They provide comprehensive ridership data, enabling passenger-centric evaluation and impact analysis. In contrast to survey data, this information is collected for all times of day and days of the year. Analysts can evaluate the behavior of a panel of individuals over time, including before and after a redesign.

Agencies like Boston’s MBTA, Washington Metropolitan Area Transit Agency (WMATA), and New York City Transit (NYCT) have applied methods to AFC and automated vehicle location (AVL) data to infer complete passenger journeys within their transit system. This origin-destination level data allows for analysis of passenger transfer behavior and path choice. In the future, agencies are likely to draw on new data sources from other modes including driving, Transportation Network Companies (TNCs), and bike sharing.

Data and Network Design in Practice

For Transport for London, Cecilia Viggiano of EDR Group developed a framework for applying AFC data to efficiently identify opportunities for valuable bus network revisions. The framework defines metrics to identify origin-destination (OD) pairs with significant potential for improvement, based on complete journeys inferred from AFC and AVL data. Improvable OD pairs are characterized by long travel times and distances relative to driving, and multi-stage journeys. Based on expected demand and benefits, this methodology groups improvable OD pairs into corridors that are candidates for new bus service.

A key component of bus corridors is the density of demand to support bus service. In the London network, 11 corridors had sufficient demand and expected benefits to justify new service. Interestingly, these corridors would serve less than 10% of the demand from the improvable OD pairs. The remaining improvable OD pairs were spread across London with a lack of density to support new bus service. Transit agencies that want to serve lower demand density trips may find solutions in other modes, such as microtransit or on-demand services.

Can Data Solve All Our Planning Problems?

Discussions about data-driven planning often ask whether data can replace planner knowledge and experience. The answer is no. The framework developed for Transport for London uses planner-defined parameters, which can be specified based on conditions in the network and planning priorities. Planner expertise and public feedback are important inputs to the decision-making process. Data-driven analysis should be treated as a tool to help reveal information planners wouldn’t otherwise know and provide evidence and justification for decisions. Because these methods can be automated, they can enable planners to regularly monitor networks and consider more frequent network and service changes, which can help transit adapt in the changing mobility environment.

Interested in more innovative uses of new transportation data? EDR Group used new vehicle speed data to evaluate the effectiveness of different incident management systems on rural highways. Urban streets may also soon be candidates for these types of analysis as more and more powerful tools become available.

About the author

Dr. Cecilia Viggiano is a Research Associate at EDR Group. She helps lead the firm’s public transit practice and contributes to transportation research and analysis across modes. Her work includes the development of multi-modal urban accessibility metrics and analysis of the impacts of demographic trends and policies on mobility patterns, including shared mobility. She has conducted assessments of public and private, local, state, and national data sources for applications including incident analysis and capital project prioritization. Cecilia has contributed to white papers and reports for APTA, TRB, and several local and state transportation agencies.

Latest Blogposts

I recently participated in a workforce roundtable at The Council for Community and Economic Research's (C2ER’s) annual conference in Atlanta. C2ER is a membership organization comprised of economic researchers and data providers from the public, pri...

Kyle Schroeckenthaler of EDR Group is on assignment to the offices of our parent company, EBP, in Zurich for the summer months. While in Zurich, Kyle is working closely with the Resources, Energy and Climate division as well as the Transportat...

The Transportation Research Board's (TRB's) National Cooperative Research Highway Research Program (NCHRP) recently released Report 873: Guidebook to Funding Transportation Through Land Value Return and Recycling. With ongoing conversations at every...

The I-TED Conference on Transportation and Economic Development has now concluded. Judging by the reaction of all the participants with whom I’ve spoken, it was a tremendous success. Here are some personal observations. The field of Transporta...

The transportation ecosystem is changing rapidly. Individuals have new transportation options, and nationwide trends show transit ridership in decline . New technologies, such as automated vehicles, are expected to continue to reshape mobility in th...